@phdthesis{Chen2016,
  author    = {Chen, Kejie},
  title     = {Real-time GNSS for fast seismic source inversion and tsunami early warning},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-93174},
  school      = {Universit{\"a}t Potsdam},
  pages     = {xii, 81},
  year      = {2016},
  abstract  = {Over the past decades, rapid and constant advances have motivated GNSS technology to approach the ability to monitor transient ground motions with mm to cm accuracy in real-time. As a result, the potential of using real-time GNSS for natural hazards prediction and early warning has been exploited intensively in recent years, e.g., landslides and volcanic eruptions monitoring. Of particular note, compared with traditional seismic instruments, GNSS does not saturate or tilt in terms of co-seismic displacement retrieving, which makes it especially valuable for earthquake and earthquake induced tsunami early warning. In this thesis, we focus on the application of real-time GNSS to fast seismic source inversion and tsunami early warning. Firstly, we present a new approach to get precise co-seismic displacements using cost effective single-frequency receivers. As is well known, with regard to high precision positioning, the main obstacle for single-frequency GPS receiver is ionospheric delay. Considering that over a few minutes, the change of ionospheric delay is almost linear, we constructed a linear model for each satellite to predict ionospheric delay. The effectiveness of this method has been validated by an out-door experiment and 2011 Tohoku event, which confirms feasibility of using dense GPS networks for geo-hazard early warning at an affordable cost. Secondly, we extended temporal point positioning from GPS-only to GPS/GLONASS and assessed the potential benefits of multi-GNSS for co-seismic displacement determination. Out-door experiments reveal that when observations are conducted in an adversary environment, adding a couple of GLONASS satellites could provide more reliable results. The case study of 2015 Illapel Mw 8.3 earthquake shows that the biases between co-seismic displacements derived from GPS-only and GPS/GLONASS vary from station to station, and could be up to 2 cm in horizontal direction and almost 3 cm in vertical direction. Furthermore, slips inverted from GPS/GLONASS co-seismic displacements using a layered crust structure on a curved plane are shallower and larger for the Illapel event. Thirdly, we tested different inversion tools and discussed the uncertainties of using real-time GNSS for tsunami early warning. To be exact, centroid moment tensor inversion, uniform slip inversion using a single Okada fault and distributed slip inversion in layered crust on a curved plane were conducted using co-seismic displacements recorded during 2014 Pisagua earthquake. While the inversion results give similar magnitude and the rupture center, there are significant differences in depth, strike, dip and rake angles, which lead to different tsunami propagation scenarios. Even though, resulting tsunami forecasting along the Chilean coast is close to each other for all three models. Finally, based on the fact that the positioning performance of BDS is now equivalent to GPS in Asia-Pacific area and Manila subduction zone has been identified as a zone of potential tsunami hazard, we suggested a conceptual BDS/GPS network for tsunami early warning in South China Sea. Numerical simulations with two earthquakes (Mw 8.0 and Mw 7.5) and induced tsunamis demonstrate the viability of this network. In addition, the advantage of BDS/GPS over a single GNSS system by source inversion grows with decreasing earthquake magnitudes.},
  language  = {en}
}
@phdthesis{Antonoglou2024,
  author    = {Antonoglou, Nikolaos},
  title     = {GNSS-based remote sensing: Innovative observation of key hydrological parameters in the Central Andes},
  doi       = {10.25932/publishup-62825},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-628256},
  school      = {Universit{\"a}t Potsdam},
  pages     = {xxii, 116},
  year      = {2024},
  abstract  = {The Central Andean region is characterized by diverse climate zones with sharp transitions between them. In this work, the area of interest is the South-Central Andes in northwestern Argentina that borders with Bolivia and Chile. The focus is the observation of soil moisture and water vapour with Global Navigation Satellite System (GNSS) remote-sensing methodologies. Because of the rapid temporal and spatial variations of water vapour and moisture circulations, monitoring this part of the hydrological cycle is crucial for understanding the mechanisms that control the local climate. Moreover, GNSS-based techniques have previously shown high potential and are appropriate for further investigation. This study includes both logistic-organization effort and data analysis. As for the prior, three GNSS ground stations were installed in remote locations in northwestern Argentina to acquire observations, where there was no availability of third-party data. The methodological development for the observation of the climate variables of soil moisture and water vapour is independent and relies on different approaches. The soil-moisture estimation with GNSS reflectometry is an approximation that has demonstrated promising results, but it has yet to be operationally employed. Thus, a more advanced algorithm that exploits more observations from multiple satellite constellations was developed using data from two pilot stations in Germany. Additionally, this algorithm was slightly modified and used in a sea-level measurement campaign. Although the objective of this application is not related to monitoring hydrological parameters, its methodology is based on the same principles and helps to evaluate the core algorithm. On the other hand, water-vapour monitoring with GNSS observations is a well-established technique that is utilized operationally. Hence, the scope of this study is conducting a meteorological analysis by examining the along-the-zenith air-moisture levels and introducing indices related to the azimuthal gradient. The results of the experiments indicate higher-quality soil moisture observations with the new algorithm. Furthermore, the analysis using the stations in northwestern Argentina illustrates the limits of this technology because of varying soil conditions and shows future research directions. The water-vapour analysis points out the strong influence of the topography on atmospheric moisture circulation and rainfall generation. Moreover, the GNSS time series allows for the identification of seasonal signatures, and the azimuthal-gradient indices permit the detection of main circulation pathways.},
  language  = {en}
}